Depression is an all-too-common psychiatric condition that can profoundly affect a person’s well-being. While there is a huge range of medications available to treat depression, many people don’t respond to the first or even second medications they are prescribed. As a result, doctors must often take a trial-and-error approach, meaning it could take months or even years to find an effective medication.

In the search for better approach, some researchers are exploring the use of machine learning to predict which patients will respond to a specific antidepressant medication. In a study published 12 September in IEEE Transactions on Biomedical Engineering, one team describes a machine-learning algorithm that analyzes the electrical activity of people’s brains and could predict response to the antidepressant Sertraline with 83.7 percent accuracy.